Machine Learning Scientist

Posted on 7/19/2023

INACTIVE

11-50 employees

ML precision delivery healthcare company

Company Overview

HEALTH[at]SCALE is on a mission to usher in a new era of care that is proactive, personalized, and precise. HEALTH[at]SCALE is a healthcare machine intelligence company that uses proprietary advances in artificial intelligence and machine learning to optimize care delivery for individuals by empowering at-risk payers, employers and providers.

Data & Analytics

Social Impact

Cybersecurity

AI & Machine Learning

Financial Services

Consumer Goods

Company Stage

Series A

Total Funding

$16M

Founded

2015

Headquarters

San Jose, California

Growth & Insights

Headcount

6 month growth

↓ -8%

1 year growth

↑ 0%

2 year growth

↑ 40%

Locations

San Jose, CA, USA

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

Data Structures & Algorithms

Java

C/C++

Python

CategoriesNew

AI & Machine Learning

Software Engineering

Requirements

PhD in Computer Science, Statistics or related technical field
Track record of publishing in top-tier machine learning and AI conferences and journals (e.g., NeurIPS, ICML, AAAI, ICDM, KDD, JMLR) with the ability to clearly describe the corresponding research contributions
2+ years of experience with machine learning in academia or industry
Strong mathematical and conceptual understanding of machine learning and AI
Familiarity with modern machine learning and optimization toolkits
Strong proficiency in Python (preferred), Java or C/C++
Excellent communication skills

Responsibilities

Research machine learning and artificial intelligence advances in core product areas
Identify key opportunities to drive greater accuracy and actionability for the company's machine intelligence technologies
Design and implement new machine intelligence algorithms that support our mission of providing context-aware, real-time, and personalized healthcare decision-support
Investigate methodological advancements leading to improved computational efficiency and scalability of learning approaches
Design and conduct structured experiments to evaluate and improve new approaches
Work closely with engineers to implement advances into production-ready systems and applications
Engage with internal and external stakeholders to define opportunities and constraints

Health at Scale is the market leader in precision health -- digital health programs that offer smart, hyper-personalized insights to help individuals choose the best providers, treatments, care settings and lifestyle choices for their unique healthcare needs. Founded by leading machine learning and clinical faculty from MIT, Stanford, Harvard and the University of Michigan, we work with some of the largest payers, employers and providers in the U.S. to improve outcomes, costs, access, and equity for their members. Health at Scale operates some of the largest deployments of AI in healthcare to date, covering millions of lives in production settings. We have been recognized for our innovation and as one of the fastest growing private companies by Forbes, Fast Company, Inc 500, UCSF Digital Health, Becker’s, TechCrunch, Bloomberg and MIT News. For more information, please visit our website.

As a machine learning scientist at Health at Scale, you will work with an exceptional team of engineers, scientists, and clinicians to conduct focused research on new machine learning approaches that advance the company’s core product capabilities and the impact we deliver to customers. You will work closely with our engineers and data scientists to identify key opportunities to augment the algorithmic intelligence in each of our products, develop and evaluate new technologies for improvement, and put successful prototypes into production.

Responsibilities

Research machine learning and artificial intelligence advances in core product areas
Identify key opportunities to drive greater accuracy and actionability for the company’s machine intelligence technologies
Design and implement new machine intelligence algorithms that support our mission of providing context-aware, real-time, and personalized healthcare decision-support
Investigate methodological advancements leading to improved computational efficiency and scalability of learning approaches
Design and conduct structured experiments to evaluate and improve new approaches
Work closely with engineers to implement advances into production-ready systems and applications
Engage with internal and external stakeholders to define opportunities and constraints

Requirements

PhD in Computer Science, Statistics or related technical field
Track record of publishing in top-tier machine learning and AI conferences and journals (e.g., NeurIPS, ICML, AAAI, ICDM, KDD, JMLR) with the ability to clearly describe the corresponding research contributions
2+ years of experience with machine learning in academia or industry
Strong mathematical and conceptual understanding of machine learning and AI
Familiarity with modern machine learning and optimization toolkits
Strong proficiency in Python (preferred), Java or C/C++
Excellent communication skills

Health at Scale is an equal opportunity employer and is committed to diversity in its hiring and business practices. To all recruitment agencies: Health at Scale does not accept agency resumes. Please do not forward resumes to this job alias, company employees or any organization location. Health at Scale is not responsible for any fees related to unsolicited resumes.